title: High predictive accuracy of an unbiased proteomic profile for sustained virologic response in chronic hepatitis C patients.
abstract: Chronic hepatitis C (CHC) infection is a leading cause of endstage liver disease. Current standard-of-care (SOC) interferon-based therapy results in sustained virological response (SVR) in only one-half of patients, and is associated with significant side effects. Accurate host predictors of virologic response are needed to individualize treatment regimens. We applied a label-free liquid chromatography mass spectrometry (LC-MS)-based proteomics discovery platform to pretreatment sera from a well-characterized and matched training cohort of 55 CHC patients, and an independent validation set of 41 CHC genotype 1 patients with characterized IL28B genotype. Accurate mass and retention time methods aligned samples to generate quantitative peptide data, with predictive modeling using Bayesian sparse latent factor regression. We identified 105 proteins of interest with two or more peptides, and a total of 3,768 peptides. Regression modeling selected three identified metaproteins, vitamin D binding protein, alpha 2 HS glycoprotein, and Complement C5, with a high predictive area under the receiver operator characteristic curve (AUROC) of 0.90 for SVR in the training cohort. A model averaging approach for identified peptides resulted in an AUROC of 0.86 in the validation cohort, and correctly identified virologic response in 71% of patients without the favorable IL28B "responder" genotype.
  
  
  CONCLUSIONS
  Our preliminary data indicate that a serum-based protein signature can accurately predict treatment response to current SOC in most CHC patients.
authors.affiliation: Duke Clinical Research Institute, Duke University, Durham, NC 27715, USA. keyur.patel@duke.edu
authors.forename: Keyur
authors.initials: K
authors.lastname: Patel
authors.forename: Joseph E
authors.initials: JE
authors.lastname: Lucas
authors.forename: J Will
authors.initials: JW
authors.lastname: Thompson
authors.forename: Laura G
authors.initials: LG
authors.lastname: Dubois
authors.forename: Hans L
authors.initials: HL
authors.lastname: Tillmann
authors.forename: Alexander J
authors.initials: AJ
authors.lastname: Thompson
authors.forename: Diane
authors.initials: D
authors.lastname: Uzarski
authors.forename: Robert M
authors.initials: RM
authors.lastname: Califf
authors.forename: Martin A
authors.initials: MA
authors.lastname: Moseley
authors.forename: Geoffrey S
authors.initials: GS
authors.lastname: Ginsburg
authors.forename: John G
authors.initials: JG
authors.lastname: McHutchison
authors.forename: Jeanette J
authors.initials: JJ
authors.lastname: McCarthy
mesh_terms: D000998:Antiviral Agents / Q000627:therapeutic use*; D001798:Blood Proteins / Q000378:metabolism; D015331:Cohort Studies; D003182:Complement C5 / Q000378:metabolism; D005838:Genotype; D019698:Hepatitis C, Chronic / Q000097:blood* / Q000188:drug therapy* / Q000235:genetics; D006801:Humans; D007372:Interferons / Q000627:therapeutic use*; D007378:Interleukins / Q000235:genetics; D015233:Models, Statistical; D040081:Protein Array Analysis; D040901:Proteomics; D012372:ROC Curve; D012044:Regression Analysis; D012680:Sensitivity and Specificity; D016896:Treatment Outcome; D014809:Vitamin D-Binding Protein / Q000097:blood; D060749:alpha-2-HS-Glycoprotein; D000095022:Interferon Lambda
chemical_list: D000998:Antiviral Agents; D001798:Blood Proteins; D003182:Complement C5; D007372:Interferons; D007378:Interleukins; D014809:Vitamin D-Binding Protein; D060749:alpha-2-HS-Glycoprotein; C556354:AHSG protein, human; C000624353:interferon-lambda, human; D000095022:Interferon Lambda